of few hours. Keywords: Encryption, Decryption, Fuzzy PN Sequence, Fuzzy Random Index. Generator, Scrambling, Difference of Quantized DC Coefficient. 1.
JPEG IMAGE ENCRYPTION USING FUZZY PN SEQUENCES
B. K. Shreyamsha Kumar and Chidamber R Patil
© Springer-Verlag London Limited 2009 This paper was published in Springer’s Signal, Image and Video Processing Journal and the original publication is available at www.springerlink.com (DOI:10.1007/s11760-009-01316). Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for commercial purposes, or modification of the content of the paper are prohibited and require prior specific permission and/or a fee.
Cite this article as: B. K. Shreyamsha Kumar and Chidamber R. Patil, “JPEG Image Encryption using Fuzzy PN Sequences”, Signal, Image and Video Processing, Vol. 4, No. 4, pp. 419-427, 2010, DOI:10.1007/s11760-009-0131-6.
Signal, Image and Video Processing, Vol. 4, No. 4, pp. 419-427, 2010 Available Online DOI: 10.1007/s11760-009-0131-6
JPEG IMAGE ENCRYPTION USING FUZZY PN SEQUENCES B.K. Shreyamsha Kumar and Chidamber R Patil Central Research Laboratory, Bharat Electronics, Bangalore-560013, INDIA E-Mail: {shreyamshakumarbk, chinnapparajappapati}@bel.co.in Phone: +91-80-28381125, Fax: +91-80-28381168 ABSTRACT The recent explosion in multimedia and networking application places a great demand on efficient transmission of images at low bit rate with high security. Mixing several existing standard encryption techniques with image encoding tends to change the compression ratio greatly. In this paper, a novel image encryption algorithm is embedded as a part of JPEG image encoding scheme to meet three major necessities: 1) To provide temporal security against casual observer 2) To preserve the compression ratio 3) Remain compliant with the JPEG file format. In the proposed algorithm, the modified DCT blocks are confused by a fuzzy PN sequence. In addition to that, the DCT coefficients of each modified DCT block are converted to unique uncorrelated symbols, which are confused by another fuzzy PN sequence. Finally, the variable length encoded bits are encrypted by chaotic stream cipher. An amalgamation of all the three techniques with random combination of seeds will provide the required security against the casual listener/observer where the security needed is only in-terms of few hours. Keywords: Encryption, Decryption, Fuzzy PN Sequence, Fuzzy Random Index Generator, Scrambling, Difference of Quantized DC Coefficient. 1. INTRODUCTION The global information sharing offered by the advances in network communications has caused a multitude of security threats for storing and transmission of multimedia content. In order to store and/or transmit the sensitive information like text, speech and image securely over wireless/computer networks, encryption is vital, which is the main focus of the present work. In encryption, the information under consideration is converted from the comprehensible form to incomprehensible one and back again at the other end, rendering it unreadable by the eavesdroppers without the secret knowledge (secret key, encryption/decryption algorithm). In today’s highly computerized and interconnected world, the security of digital images/video has become increasingly more significant in applications such as pay-perview TV, confidential video conferencing, medical imaging and in industrial or military imaging systems. In order to fulfill such a task, many different image encryption techniques have been proposed in the literature. They include Bit Recirculation Image Encryption [1], Infinite Series Convergence method [2], Fuzzy PN code based Color Image Encryption method [3], Combinational Permutation method [4], Magnitude and Phase Manipulation method [5], SCAN based methods [6, 7] and Chaos based methods [8, 9, 10, 11]. Further, image encryption based on phase encoding by means of a fringe pattern uses cosine function, which adds to its argument the image to be encrypted as a phase [27]. Since these methods manipulate an entire data set without any presumption
Springer
Signal, Image and Video Processing,
about compression at later time, the secure transmission of image has become more costly in terms of time, bandwidth and complexity. Thus, users pay a price for security proportional to their desired level of security. Further, the use of compression after encryption [12] fails to exploit the spatial and psycho-visual redundancies efficiently as the encryption of an uncompressed image removes intelligibility from the original image and hence incurring compression penalties. This results in a tradeoff between the competing requirements of encryption and compression. However for efficient secure image transmission, a system of encryption is required that works cooperatively with compression scheme ensuring the security of the image [13, 14, 15, 16, 17]. Vector Quantization based image encryption proposed by Chen [13] encrypts both the quantization table and code stream at the same time with high security. Further, Cheng proposed image encryption based on SPHIT encoding [14] that encrypts only the wavelet zero-tree keeping the compression ratio unchanged. The encryption of JPEG compressed image may be realized by encrypting the quantization tables, Huffman tables for secure image transmission over bandwidth constrained network. But, this is vulnerable to attackers as the quantization tables or Huffman tables can be recreated by the various tests. Further, the encryption of DCT coefficients causes a great change in compression ratio, as it changes the statistics of DCT coefficients. In JPEG standard [18], the AC Huffman code word depends on the number of zeros preceding the non-zero AC coefficient as well as the magnitude category of the non-zero AC coefficient. These code words are followed by appended bits that fully specify the sign and magnitude of the non-zero coefficients. In [15, 17], only the appended bits corresponding to a selected number of AC coefficients are encrypted to preserve the overall bit rate and to remain compliant with JPEG file format. The use of Advanced Encryption Standard (AES) cipher to encrypt the selected DCT coefficients [16] provides satisfactory PSNR, sufficient security and acceptable confidentiality but at the cost of complexity and time. In [19], DCT blocks, DCT coefficients and sign bit of the DCT coefficients are confused by pseudo-random Space Filling Curves (SFC) [20, 21, 22] affecting the compression ratio slightly. For secure image communication, security is needed against two types of attackers, namely, casual listeners/observers or professional unauthorized recipients/ cryptanalysts. If the security needed is against the casual listeners/observers, encryption scheme should be unbreakable for few hours (temporal security) where as for cryptanalysts, it should be unbreakable for many years. For the scenario where security is needed against casual listener/observer, cryptographic structure should be as simple as possible in order to reduce the cost and should work cooperatively with compression scheme to utilize the bandwidth efficiently. Hence the present work focuses on the development of simple image encryption technique that work considerately with JPEG compression for providing security against such casual observers in the context of image communications without change in compression ratio. The paper is organized as follows: Section 2 deals with image encryption based on scrambling. Section 3 discusses the proposed JPEG image encryption algorithm in detail. Section 4 discusses experimental results followed by conclusions in Section 5.
2
Springer
B.K. ShreyamshaKumar and Chidamber R Patil
2. IMAGE ENCRYPTION BASED ON SCRAMBLING A rearrangement {q i i = 1,2,...., n, q i ∈ S } of { p i i = 1,2,...., n, pi ∈ S } is called a permutation/scrambling of degree n, where S denotes any non-empty set. This permutation can be written as p p ...... p n ϕ = 1 2 (1) q1 q 2 .......q n where n! such permutations are possible and the reverse of this permutation process is called descrambling and is represented as q q .......q n ϕ −1 = 1 2 (2) p1 p 2 ...... p n which retrieves the original arrangement. In this process of scrambling, only the positions of the elements are changed. The encryption process with the help of scrambling/permutation can be defined for any data matrix X as (3) ψ = ϕ n (ϕ n −1 (...(ϕ1 ( X ))...) where, ψ is a cipher matrix with n different permutations ϕ 1, ϕ 2 ,...,ϕ n sequentially and can be restored again with the inverse operation of ϕ i (i = 1,2,..., n) in inverse sequence, i.e., X = ϕ1−1 (ϕ 2−1 (...(ϕ n−1 (ψ ))...) (4) Such a process, when applied in tandem with the random permutation generators, can provide better security in terms of any kind of attack, provided ϕ i (i = 1,2,..., n) are chosen randomly from any standard set of permutations. As the combination of these permutations approaches redundancy, visual intelligence reduces. To get back the original image at the receiver, the order of the permutation processes should be exactly reverse to the order at the transmitter, otherwise the output will produce corrupted image with no visual information. Therefore, this random combination seed is also sent to destination via secured communication channel. 2.1. Fuzzy Random Index Generator In designing private key cryptographic techniques, Pseudo random Noise (PN) sequence generator is considered as an important building block for scrambling/ permutation purpose and is usually constructed using the linear feedback shift registers [23, 24]. Recently a new method for generating PN sequence based on Fuzzy logic has been proposed in [25] and thus generated PN sequences are used by a Fuzzy Random Index Generator (FRIG) to generate Random Indices as shown in Fig. 1. The fuzzy system rules are constructed using numerical data pairs during the training stage and then combined with linguistic information to form the working if-then rules. Also, a learning procedure is applied to copy the behavior of real random source before generating the PN sequences. Although the generated PN sequences support all the properties of random sequences, they are deterministic and their lengths can be made arbitrary long [3, 25]. That is, they can be exactly regenerated by fixing the parameters of the PN sequence generator. On the other hand, the change of initial seed generates an
3
Springer
Signal, Image and Video Processing,
Binary to Decimal Converter
Random Indices
PN Sequence Generator
Initial Seed (Transmitted Through Secure Channel)
Fig.1 Structure of Fuzzy Random Index Generator entirely new PN sequence. Thus generated PN sequences are used for data encryption, image encryption [3] and secure direct-sequence spread-spectrum communication [25]. These PN sequences are passed through binary to decimal converter to generate Random Indices.
3. JPEG IMAGE ENCRYPTION SCHEME The proposed scheme permutes the modified DCT blocks by a sequence of random indices generated from FRIG, confuses uncorrelated unique symbols obtained after Run Length Encoding (RLE) and encrypt the bits obtained from Variable Length Coding (VLC) by a chaotic stream cipher with no change in compression ratio. The block diagram of the proposed method is shown in Fig. 2. As the PN sequence generator used to generate random indices provides high security, which has been proved in [25], the proposed algorithm also provides the same level of security. Further, the seeds S1, S2, S3 used to generate PN sequence is chosen randomly to increase the security level.
Image
Sequence of Random Indices (S1)
Sequence of Random Indices (S2)
PN Sequence (S3)
Block Scrambling
Scrambled Symbol Coding
Stream Ciphering
Encrypted Data
Fig. 2 JPEG Encryption Scheme 3.1. Block Scrambling In Block Scrambling, the given image is divided into blocks of size 8x8 and is level shifted by 2n-1, where 2n is the maximum number of gray levels [18, 26]. Afterwards, the DCT of each block is computed and then quantized using a standard JPEG quantization matrix. The difference between the current and previous block’s quantized DC coefficient is calculated and is called as Difference of Quantized DC (DQDC) coefficient. The resulting DQDC coefficient is stored at the current block’s DC coefficient position and the process is repeated for all the blocks except for the first
4
Springer
B.K. ShreyamshaKumar and Chidamber R Patil
block. For the first block, the DQDC coefficient is replaced with its quantized DC coefficient with the assumption that quantized DC coefficient of previous block is zero. Further, the position of these modified DCT blocks are scrambled in accordance with the random index sequence generated from FRIG with initial seed of S1 (Fig. 3(a)). Since the difference between quantized DC coefficients is computed before the block scrambling, the correlation among DC coefficients of adjacent blocks are still exploited and hence the compression ratio is retained as that of JPEG. For better encryption, block size should be smaller so that the objects and its edges don’t appear clearly. The intended receiver knows the structure of FRIG as well as the initial seed, which is transmitted to the intended receiver through a secured channel and hence, can unscramble the DCT blocks to get back the image. As the security is needed only interms of few hours (temporal security), by the time casual listener/observer breaks this, the information is of no importance. To explain the method clearly, an image of size 64x64 is considered and is divided into 64 blocks each of size 8x8. The DCT of these blocks are computed, quantized and numbered as in Fig. 3(b). Now the DQDC coefficient is obtained by computing the difference between 2nd and 1st block’s quantized DC coefficients. Further, the 2nd block’s quantized DC coefficient is replaced with previously computed DQDC coefficient keeping the quantized AC coefficients unchanged to get modified DCT block of block 2. This is repeated for all the blocks numbered from 2 to 64 except for the 1st block, where the both DC and AC coefficients are retained. If the random index sequence generated from FRIG with initial seed of S1 is (3, 10, 59, … ), then the 3rd block in Fig. 3(b) is coded first followed by 10th, 59th and so on. Image
8x8 Blocks
Scrambled Scrambling Blocks Sequence of Random Indices (S1)
DCT
Quantization
DQDC Computation
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64
(a)
(b)
Fig. 3 (a) Block Scrambling and (b) Block Numbering 3.2 Scrambled Symbol Coding DCT compacts energy at low frequencies where most important visual characteristics of the image are placed while the details are situated in high frequencies. The human visual system is more sensitive to lower frequencies than at higher frequencies [16]. As DC coefficients carry important visual information and are highly predictable, it is not effectual to encrypt/scramble the DC coefficients. Scrambling the 63 quantized DCT coefficients of an 8x8 block changes the coefficient distribution affecting the bit rate and hence scrambling is not advisable at this stage. The quantization of the DCT coefficients produces a large number of zero-valued coefficients, which are aggregated into runs of zeros after zigzag scanning. In JPEG standard [18], the DC coefficient is difference coded relative to the DC coefficient of the previous block to exploit the 5
Springer
Signal, Image and Video Processing,
correlation among DC coefficients. Further, the zigzag ordered AC coefficients are RLE coded to aggregate the zero coefficients into runs of zeros and then VLC coded. The VLC code appends the bits that fully specify the sign and magnitude of the nonzero AC coefficients to the code words. The appended bits of selected AC coefficients are encrypted as in [15, 17] without affecting the code words, as they are essential for synchronization and so as not to interfere with the decoding process (to remain compliant with JPEG bitstream). In [19], the quantized DCT coefficients are divided into four subsections and AC coefficients in each subsection are confused leaving the DC coefficient unaffected, as DC coefficient is highly predictable. This will affect the bit rate as run lengths are compromised. Hence scrambling cannot be done until RLE, to keep the compression ratio intact. In the proposed method, the run of zeros along with the non-zero AC coefficient that terminate the run is treated as one unique symbol (Fig. 4(a)) and these symbols are scrambled using a random index sequence generated with initial seed of S2 (Fig. 4(b)), leaving the position of the DQDC coefficient unchanged. In Fig. 4(a), DC and Sb denotes DQDC coefficient and symbols respectively. Further, all the scrambled symbols including unscrambled DQDC coefficient are encoded as in JPEG standard. The number of symbols in each modified DCT block mainly depends on the number of non-zero AC coefficients, which may vary depending on the quantization matrix. If the random index value selected from the random index sequence is greater than /equal to total number of symbols in the current block, then next random index value is considered for scrambling. For example, the total number of symbols with in the block is 15 and the random index sequence generated from FRIG is {…, 12, 16, 17, 5, …}, then there are no 16th, 17th symbols to code. In that case, 5th symbol is coded after 12th symbol neglecting 16th and 17th. -26 -3
1
-2
DC Sb1 Sb2 Sb3
0
0
Sb3
-1
2
0
Sb4
0
0
0
0
Sb5
-1
-1 EOB
Sb6
(a) Scrambled Blocks Sequence of Random Indices (S2)
Zigzag
RLE
Unique Symbol Conversion
Scrambling
DC Coding or VLC Coding
JPEG Encrypted Bitstream
(b) Fig. 4 (a) Symbol Conversion (b) Scrambled Symbol Coding
6
Springer
B.K. ShreyamshaKumar and Chidamber R Patil
The proposed algorithm processes all the 8x8 blocks and all the symbols in a block like JPEG except for a small change, that is, the blocks and symbols in a block are processed randomly. The generation of fuzzy random indices for random selection of blocks and symbols adds some complexity to the proposed algorithm keeping the memory as well as computational time almost similar to that of JPEG.
3.3 Stream Ciphering of VLC Encoded Bits In this step, JPEG encrypted bitstream from the Scrambled Symbol Coding is encrypted using a stream cipher by employing another fuzzy PN sequence generated with an initial seed of S3 (Fig. 5). Stream cipher is more suitable for encryption as it retains the bit rate rather than block cipher, which has a tendency of increasing the bit rates. This step provides additional security along with the Block Scrambling and Scrambled Symbol Coding. Note that JPEG header is not encrypted to keep the JPEG file format intact for any JPEG decoder to decode. JPEG Encrypted Bitstream
+
Encrypted Data
PN Sequence (S3)
Fig. 5 Stream Ciphering 4. RESULTS AND DISCUSSIONS The proposed JPEG encryption technique is applied to various images and the encrypted images are all too chaotic to be understood. All the images used for simulations are of size 256x256 and are divided into blocks of size 8x8 for processing. Among them, simulation results for Barbara, Cameraman and AV-8 Harrier Aircraft are shown in Fig.6 where, (a) shows the original image, (b), (c), (d) shows the JPEG encrypted images, and (e) shows the JPEG decrypted image. The standard JPEG decoding of block scrambled image is shown in Fig. 6(b) and it is difficult to understand the garbled image without proper decryption. Further, a horizontal coherence is observed in Fig. 6(b). This is because, the DQDC coefficient is computed with respect to quantized DC coefficient of the previous block which is located horizontally, except for the blocks numbered with 1, 9, …, 49, 57 (Fig. 3(a)). From Fig. 6(a) it is noticed that image of Barbara has more edges, patterns and discontinuities (high frequency components) than uniform background (low frequency component). Whereas the image of cameraman and AV-8 Harrier Aircraft (Fig. 6(a)) has more area of uniform background along with some high frequency components like edges, patterns and discontinuities. For all these images, the proposed block scrambling has worked well irrespective of its spatial frequency distribution (Fig. 6(b)). Fig. 6(c) shows the standard JPEG decoding of the symbol encrypted image. In Fig. 6(c) of Barbara, her face, the design of her cloths as well as table cloth and books on rack are not identifiable. Also, Fig. 6(c) of cameraman does not have details of buildings and his face is not recognizable, and Fig. 6(c) of AV-8 Harrier Aircraft does not have details of mountains. Further it is observed that, the uniform background in the original image of cameraman and AV-8 Harrier Aircraft (Fig. 6(a)) has been preserved 7
Springer
Signal, Image and Video Processing,
(a)
(b)
(c)
(d)
(e)
Fig. 6 Results for Barbara, Cameraman and AV-8 Harrier Aircraft, (a) Original Image, (b) Block Scrambled Image, (c) Symbol Scrambled Image, (d) Blend of Block and Symbol Scrambled Image, (e) Decrypted Image. in the symbol scrambled images (Fig. 6(c)). Particularly, symbol scrambling encrypts the edges, patterns and discontinuities (high frequency information) in the image well,
8
Springer
B.K. ShreyamshaKumar and Chidamber R Patil
while leaving the uniform background as it is. This is because, the position of DQDC coefficient of every DCT block is not scrambled as it carries important visual information and is highly predictable. The blend of both block scrambling (Fig.6 (b)) as well as symbol scrambling (Fig. 6(c)) gives still better results compared to individual scrambling and standard JPEG decoding of the same is shown in Fig. 6(d). Further, Fig. 6(b) is equivalent to symbol decryption of Fig. 6(d) and Fig. 6(c) is equivalent to block decryption of Fig. 6(d). It is observed that, the encrypted ones cannot be understood at all, which shows that the proposed JPEG encryption scheme is sufficient for providing temporal security against casual listener/observer. Further, the security of the system depends on the fuzzy PN sequence generator and has been proved in [25]. To get back the original image properly (Fig. 6(e)), the proposed JPEG encryption algorithm has to be traced back with proper and respective seeds. From Figs. 6(a) and 6(e) it is evident that, the original and JPEG decrypted images look alike except for quantization error because of quantization. The histograms of original (Barbara, Cameraman, AV-8 Harrier Aircraft) and encrypted (blend of block and symbol scrambling) images are shown in Fig.7 and is observed that the histogram of encrypted image is almost flat/spread compared to that of the original. The histogram of the image tells about the contrast of the image as well as the gray level statistics of an image. If the histogram is flat, image has good contrast with all details visible and it also signifies that, the occurrence of all gray values is equally probable. Even with good contrast, it is unfeasible to pick out the information within the gibberish image shown in Fig. 6(d). Since the histogram of the encrypted image is almost uniform random distribution of gray levels (Fig. 7), the proposed algorithm provides better results against the statistical analysis attack.
1500
Pixel Occurrences
(a)
400
200 0
0
100
200
(b)
1000 500 0 0
100
Pixel Values
200
Pixel Values
(c)
800
Pixel Occurrences
Pixel Occurrences
The compression ratio and the PSNR of the JPEG encoded images as well as that of JPEG encrypted images are tabulated in Table 1 and 2 for comparison. From Tables 1 and 2 it is evident that, the compression ratio of individual images with JPEG encoding
600
Original Encrypted
400 200 0 0
100
200
Pixel Values
Fig. 7 Histogram of Original and Encrypted Images of (a) Barbara, (b) Cameraman and (c) AV-8 Harrier Aircraft. 9
Springer
Signal, Image and Video Processing,
(column 2 of Table 1) is equal to that of JPEG encrypted images (column 2 of Table 2). That is, the proposed method retains the compression ratio of the JPEG with encryption. Further from Tables 1 and 2, it is observed that, the PSNR of JPEG decoded block scrambled image (column 3 of Table 2) and that of symbol scrambled image (column 4 of Table 2) is less compared to that of JPEG (column 3 of Table.1). It is known that, lesser the PSNR more is the noise present in the image as compared to its signal strength. Hence, it is very difficult to understand the image with more noise and this has been shown in Fig. 6(b). As the symbol scrambling encrypts high frequency information like edges, patterns and discontinuities well compared to low frequency information, the JPEG decoding of symbol encrypted images gives lesser PSNR for images having high frequency information (Baboon, Barbara) compared to that with low and medium frequency information (Shannon, Lena). Further from Table 2, PSNR of the JPEG decoded encrypted image (column 5) is almost comparable to that of block scrambled image (column 3). Also, the PSNR of JPEG decoded encrypted image (column 5 of Table.2) is less compared to that of JPEG (column 3 of Table.1). That is, JPEG decoded image (Fig. 6(d)) has more noise than signal strength and hence very difficult to understand. However, it is observed that, PSNR of JPEG images (column 3 of Table 1) is equal to that of JPEG decrypted images (column 6 of Table 2). This implies that, the original image can be retrieved back without any loss except for quantization errors (Fig. 6(e)). Table 1. Compression Ratio and PSNR of JPEG Images PSNR (in dB) Test Images Compression Ratio (column 2) (column 3) (column 1) Baboon 6.94329 23.01 Barbara 9.85578 25.406 Cameraman 13.0997 29.498 Peppers 11.7527 30.496 Shannon 15.1262 33.651 Lena 11.9156 32.56 AV-8 Harrier Aircraft 10.65 27.23 Table 2. Compression Ratio and PSNR (in dB) of JPEG Encrypted/Decrypted Images JPEG decoding of (PSNR in dB) Compression Ratio of Block Symbol Test Images Block + Symbol Decrypted Encrypted Scrambled Scrambled (column 1) Scrambled Image Image Image Image Image (column 5) (column 6) (column 2) (column 3) (column 4) Baboon 6.94329 7.34 15.06 7.31 23.01 Barbara 9.85578 5.52 15.99 5.53 25.406 Cameraman 13.0997 5.21 15.62 5.21 29.498 Peppers 11.7527 5.55 16.39 5.56 30.496 Shannon 15.1262 6.79 17.32 6.78 33.651 Lena 11.9156 6.14 17.56 6.14 32.56 AV-8 Harrier 10.65 6.33 15.76 6.33 27.23 Aircraft As the proposed JPEG encryption algorithm changes only the relative position of the modified DCT blocks and/or symbols leaving the ranges of DCT coefficients
10
Springer
B.K. ShreyamshaKumar and Chidamber R Patil
unchanged, it retains the compression ratio of JPEG. Further, the proposed algorithm controls the bit rate by changing quantization matrix like JPEG. Also, the JPEG file format is kept intact for any JPEG decoder to operate on the bitstream. As JPEG compression is involved in the encryption process, the proposed algorithm is also lossy, which depends on the quantization matrix.
5. CONCLUSIONS AND FUTURE WORK In this paper, an image encryption algorithm that works co-operatively with JPEG compression has been proposed to meet three major requirements: 1) To provide temporal security against casual observer 2) To preserve the compression ratio 3) Remain compliant with the JPEG file format. The proposed scheme employs modified DCT block scrambling, symbol scrambling and then stream ciphering to provide the temporal security against the casual listener/observer. The experimental results show that the encryption scheme provides the required security along with JPEG compression. Further, it preserves the compression ratio and the JPEG file format. All these advantages make it suitable for secure image coding and tactical communication. The future work is extension of the proposed encryption scheme to color images and its investigation to JPEG2000 compression standard as well as for digital watermarking.
Acknowledgements The authors like to acknowledge Mr. Santosh Kumar A.S, Member (Research Staff), Central Research Laboratory, Bharat Electronics, Bangalore and Mr. Rajeeva G.K, Senior Design Engineer, Good Rich Aerospace Pvt Ltd, Bangalore for useful discussion. Also, the authors would like to thank Dr. A.T. Khalghatgi, Chief Scientist, Mr. Manoj Jain and Dr. C. Ramesh, Member (Senior Research Staff), Central Research Laboratory, Bharat Electronics, Bangalore for their kind support and every possible help.
REFERENCES [1]
Yen J. C. and Guo J. I, “A New Image Encryption System and its VLSI Architecture”, IEEE Workshop on Signal Processing Systems, Taipei, pp.430437, 1999.
[2]
Balasubramanian S, “Image Encryption using Infinite Series Convergence”, Proceedings of the 18th International Conference on Systems Engineering (ISCEng), pp.257-262, Aug 2005.
[3]
El-Khamy S. E., Lotfy M. and Ali A. H, “A New Color Image Encryption Technique utilizing Fuzzy Pseudo-random Bit Generator”, Proceedings of 22nd National Radio Science Conference (NRSC), pp.185-194, Mar 2005.
[4]
Mitra A., Subba Rao Y. V. and Prasanna S. R. M, “A New Image Encryption Approach using Combinational Permutation Techniques”, International Journal of Computer Science, Vol. 1, No. 2, pp. 127-131, 2006. 11
Springer
Signal, Image and Video Processing,
[5]
Prasanna S. R. M., Subba Rao Y. V. and Mitra A, “An Image Encryption Method with Magnitude and Phase Manipulation using Carrier Images”, International Journal of Computer Science, Vol. 1, No. 2, pp. 132-137, 2006.
[6]
Bourbakis N. and Alexopoulos C, “Picture Data Encryption using SCAN Pattern”, Pattern Recognition, vol.25, no.6, pp.567-581, 1992.
[7]
Chen C. S. and Chen R. J, “Image Encryption and Decryption using SCAN Methodology”, Proceedings of seventh International Conference on Parallel and Distributed Computing, Application and Technologies (PDCAT’06), pp.61-66, 2006.
[8]
Pichler F. and Scharinger J, “Efficient Image Encryption based on Chaotic Maps”, Proceedings of 20th Workshop of the Austrian Association for Pattern Recognition, pp.159-170, Leibnitz, Austria, preprint, 1996.
[9]
Li S. and Zheng X, “Cryptanalysis of a Chaotic Image Encryption Method”, Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS’02), Vol. 2, pp. 708-711, 2002.
[10] Socek D., Li S., Magliveras S. S. and Furht B, “ Enhanced 1-D Chaotic KeyBased Algorithm for Image Encryption”, IEEE Proceedings of the First International Conference on Security and Privacy for Emerging Areas in Communications Networks (SECURECOMM’05), pp.406-408, Sep 2005. [11] Gu G. and Han G.: “An Enhanced Chaos Based Image Encryption Algorithm”, IEEE Proceedings of the First International Conference on Innovative Computing, Information and Control (ICICIC’06), Vol.1, pp.492-495, Sep 2006. [12] Gurijala A., Khayam S. A., Radha H. and Deller Jr J.R, “On EncryptionCompression Tradeoff Pre/Post-Filtered Images”, SPIE Conference on Mathematics of Data/Image Coding, Compression and Encryption VIII with Applications, San Diego CA, Vol. 5915, No. 1, pp. 591-601, Aug 2005. [13] Chen T. S., Chang C. C., and Hwang M. S, “A Virtual Image Cryptosystem based upon Vector Quantization”, IEEE Transactions on Image Processing, Vol.7, No.10, pp. 1485-1488, Oct 1998. [14] Cheng H. and Li X, “Partial Encryption of Compressed Images and Videos”, IEEE Transactions on Signal Processing, Vol. 48, No. 8, pp. 2439-2451, Aug 2000. [15] Droogenbroeck M. V, “Partial Encryption of Images for Real-Time Applications”, Proceedings of fourth Benelux Signal Processing Symposium, pp.11-15, Apr 2004. [16] Puech W. and Rodrigues J. M, “Crypto-Compression of Medical Images by Selective Encryption of DCT”, 13th European Signal Processing Conference, Sep 2005.
12
Springer
B.K. ShreyamshaKumar and Chidamber R Patil
[17] Droogenbroeck M. V. and Benedett R, “Techniques for a Selective Encryption of Uncompressed and Compressed Images”, Proceedings of Advanced Concepts for Intelligent Vision Systems (ACIVS’02), pp. 90-97, Sep 9-11, 2002. [18] Pennebaker W.B. and Mitchell J. L, “JPEG Still Image Compression Standard”, New York, Van Nostrand Reinhold, 1993. [19] Lian S., Sun J. and Wang Z, “A Novel Image Encryption Scheme Based-on JPEG Encoding”, Proceedings of the Eighth International Conference on Information Visualization, pp.217-220, Jul 2004. [20] Zeng W. and Lei S, “Efficient Frequency Domain Selective Scrambling of Digital Video”, IEEE Transactions on Multimedia, Vol. 5, No. 1, pp. 118-129, Mar 2003. [21] Dufaux F. and Ebrahimi T, “Scrambling for Video Surveillance with Privacy”, Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), pp.160-163, Jun 2006. [22] Matias Y. and Shamir A, “ A Video Scrambling Technique based on Space Filling Curves”, Proceedings of Advances in Cryptology - CRYPTO’87, Springer LNCS 293, pp. 398-417, 1987. [23] Wang L. T. and McCluskey E. J, “Linear Feedback Shift Register Design using Cyclic Codes”, IEEE Transaction on Computers, Vol. 37, No. 10, pp. 13021306, Oct 1988. [24] Fuster A. and Garcia L. J, “An Efficient Algorithm to Generate Binary Sequences for Cryptographic Purposes”, Theoretical Computer Science, 259, pp. 679-688, May 2001. [25] El-Khamy S. E., Lotfy M. and Ali A. H, “A New Fuzzy Logic based PseudoRandom Bit Generator for Secure DS-CDMA Systems”, 22nd URSI NRSC Conference, pp.377-384, Mar 2005. [26] R. C. Gonzalez and R. E.Woods, Digital Image Processing, Pearson Education (Singapore) Pte. Ltd., Delhi, India, Ch. 8, pp. 409-518, 2004. [27] J.A.M. Rodriguez and R. Rodriguez-Vera, “Image Encryption based on Phase Encoding by means of a Fringe Pattern and Computational Algorithms”, Revista Mexicana De F´Isica, Vol. 52, No. 1, pp. 53–63, Feb 2006.
13
Springer
Signal, Image and Video Processing,
Authors Biography B.K. SHREYAMSHA KUMAR received the B.E degree in Electronics and Communication Engineering from Bangalore University, India, in 2000. He received the M.Tech degree in Industrial Electronics from National Institute of Technology Karnataka, Surathkal, India, in 2004. He joined Central Research Laboratory (A Corporate Research Facility of Bharat Electronics) as a Member (Research Staff) in 2004. He has three International Journal Papers and two International Conference Papers to his credit. He is a recipient of BEL's R&D Excellence Award for his contribution on "Engine for Uncooled Thermal Imager". His areas of research include Image Processing, Harmonic Wavelets, Image Encryption, Document Image Processing, Group Delay Functions, Spectral Estimation, Time-Frequency Representation and Inverse Synthetic Aperture Radar Imaging. CHIDAMBER R PATIL received the B.E. degree in Electronics and Communication Engineering from Karnataka University, Dharwad, India in 1996. He received the M.Tech degree in Digital Electronics and Advance Communication from National Institute of Technology Karnataka, Surathkal, India in 1999. He joined Central Research Laboratory as a Member (Research Staff) in 1999. He has two International Conference Papers to his credit. He is a recipient of BEL’s R&D Excellence Award for his contribution on “Engine for Uncooled Thermal Imager”. His areas of research include Image Processing, Image Compression, Thermal Imaging, Radar Video Compression and Radar data processing.
14
Springer
